WO2020083492A1 - Codeur de canal et procédé de codage d'un mot d'information - Google Patents

Codeur de canal et procédé de codage d'un mot d'information Download PDF

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Publication number
WO2020083492A1
WO2020083492A1 PCT/EP2018/079286 EP2018079286W WO2020083492A1 WO 2020083492 A1 WO2020083492 A1 WO 2020083492A1 EP 2018079286 W EP2018079286 W EP 2018079286W WO 2020083492 A1 WO2020083492 A1 WO 2020083492A1
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WO
WIPO (PCT)
Prior art keywords
bits
parity
channel encoder
former
code
Prior art date
Application number
PCT/EP2018/079286
Other languages
English (en)
Inventor
Georg Bocherer
Ingmar LAND
Jean-Claude Belfiore
Original Assignee
Huawei Technologies Co., Ltd.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Huawei Technologies Co., Ltd. filed Critical Huawei Technologies Co., Ltd.
Priority to CN201880098682.0A priority Critical patent/CN112840581B/zh
Priority to PCT/EP2018/079286 priority patent/WO2020083492A1/fr
Publication of WO2020083492A1 publication Critical patent/WO2020083492A1/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0041—Arrangements at the transmitter end
    • H04L1/0042—Encoding specially adapted to other signal generation operation, e.g. in order to reduce transmit distortions, jitter, or to improve signal shape
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
    • H03M13/25—Error detection or forward error correction by signal space coding, i.e. adding redundancy in the signal constellation, e.g. Trellis Coded Modulation [TCM]
    • H03M13/255—Error detection or forward error correction by signal space coding, i.e. adding redundancy in the signal constellation, e.g. Trellis Coded Modulation [TCM] with Low Density Parity Check [LDPC] codes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0056—Systems characterized by the type of code used
    • H04L1/0057—Block codes
    • H04L1/0058—Block-coded modulation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/32—Carrier systems characterised by combinations of two or more of the types covered by groups H04L27/02, H04L27/10, H04L27/18 or H04L27/26
    • H04L27/34—Amplitude- and phase-modulated carrier systems, e.g. quadrature-amplitude modulated carrier systems
    • H04L27/3405—Modifications of the signal space to increase the efficiency of transmission, e.g. reduction of the bit error rate, bandwidth, or average power

Definitions

  • the present invention relates to the field of channel coding. More specifically, the present invention relates to a channel encoder and a corresponding method for encoding an information word.
  • a system for forward error correction (FEC) coding also called a coding scheme, consists of an encoder at the transmitter side and a decoder at the receiver side.
  • the encoder adds redundancy to the data to be transmitted, i.e. additional redundant data, and the decoder exploits this redundancy to correct transmission errors, such that the receiver obtains the transmitted data free of errors despite the noisy communication channel.
  • Figure 1 shows such a communication system 100, wherein the data u to be transmitted, termed information word, is given to an encoder 101 , which produces the codeword x containing redundancy. This is then transmitted over a noisy communication channel 103 which typically introduces errors.
  • the output vector y is provided to a decoder 105, which produces estimates of the transmitted codeword and the transmitted data.
  • the set C of possible codewords is called the code, or channel code, and the following is particularly concerned with such a code.
  • a code C of length N and dimension K for short, an ( N, K ) code, may be defined by a generator matrix G of size K x N ⁇
  • the code C may be defined by the parity check matrix H of size (N— K) x N ⁇
  • H T denotes the transpose of H.
  • check matrices can be determined and vice versa (see F.J. MacWilliams & N.J.A. Sloane: The Theory of Error-Correcting Codes. North-Holland Publishing, 1977).
  • H S , H p ⁇ denotes the concatenation of H s and H p .
  • the part H p is called the parity forming part and H s the syndrome forming part.
  • Systematic encoding works as follows: to a message u of length K, redundancy bits p of length N - K are appended.
  • Frequency bands for data transmission are a very expensive and restricted resource in wireless, fibre-optic and copper-cable communication.
  • higher-order modulation is required, where more than 1 bit is mapped to each real-dimensional time-frequency slot.
  • Common higher-order modulation formats are quadrature amplitude modulation (QAM) and amplitude phase-shift keying (APSK).
  • Probabilistic shaping includes mapping to a shaping set S Q F w containing sequences with desired properties. For example, the set S Q ⁇ 0,1 ⁇ 3 with the four sequences of lowest weight is
  • Arbitrary bit strings can be mapped into sequences in S by successively applying the map:
  • shaping set S is not linear, e.g., adding 001 e S and 010 e S results in Oil, which is not in the set S.
  • Mapping into shaping sets can be realized by distribution matching (DM), which refers to algorithms dedicated for this task (P. Schulte & G. Bocherer,“Constant composition distribution matching,” IEEE Trans. Inf. Theory, vol. 62, pp. 430, 2016).
  • Figure 2 shows an example of a conventional communication system 200 comprising on the side of the channel encoder a distribution matcher 201 and a FEC encoder 203.
  • Probabilistic amplitude shaping is an efficient way to combine probabilistic shaping with forward error correcting (see G. Bocherer et. al.,“Bandwidth efficient and rate- matched low-density parity-check coded modulation”, IEEE Trans. Commun., vol. 63, pp. 4651 , 2015).
  • a distribution matcher (DM) 201 serves as the shaping device, followed by a linear FEC encoder 203 (see G. Bocherer et. al., “Bandwidth efficient and rate-matched low-density parity-check coded modulation”, IEEE Trans. Commun., vol. 63, pp. 4651 , 2015).
  • the additional parity bits are transmitted when the receiver emits a NACK message. Since the parity is unshaped in probabilistic amplitude shaping, the power efficiency of the incremental redundancy is sub-optimal.
  • FEC forward error correction
  • Embodiments of the invention enable optimal transmission by providing an efficient encoder and a corresponding method to unambiguously map a message to a vector for a linear code and a non-linear shaping set, i.e., to encode an information word into a shaped codeword with shaped parity bits in an efficient manner.
  • an improved channel encoder is provided, allowing for encoding an information word into a shaped codeword with shaped parity bits in an efficient manner.
  • the channel encoder is configured to implement the probabilistic shaping scheme such that further the information word u fulfils a second shaping constraint.
  • the first shaping constraint is equal to the second shaping constraint.
  • the first shaping constraint requires that the number of 0 bits is substantially different from the number of 1 bits of the M + J parity bits p of the code word x.
  • the number of 0 bits is substantially larger than the number of 1 bits of the M + J parity bits p of the code word x, wherein the channel encoder is further configured to map the M + J parity bits p to a plurality of signal points having at least one low energy level and one high energy level by mapping the 0 bits of the M + J parity bits p to the low energy level signal points.
  • the number of 1 bits is substantially larger than the number of 0 bits of the M + J parity bits p of the code word x, wherein the channel encoder is further configured to map the M + J parity bits p to a plurality of signal points having at least one low energy level and one high energy level by mapping the 1 bits of the M + J parity bits p to the low energy level signal points.
  • the channel encoder comprises a distribution matcher, wherein the distribution matcher is configured to generate the information word u of length K - J bits on the basis of L data bits with K - ] > L.
  • the channel encoder is configured to encode the information word u of length K - J bits with K > J > 0 to a code word x of length N bits on the basis of a parity check matrix H, wherein the channel encoder is configured to use the parity check matrix H in the following form:
  • H [H S H P ] , wherein H s denotes a syndrome former of size (N - K) x ( K -/) and H p denotes a non square full row rank parity former of size (N - K) x (N - K + /).
  • the parity check matrix H defines a linear forward error correction, FEC, code such that the FEC code has good error correcting capabilities.
  • the parity check matrix H defines a low-density parity check, LDPC, code.
  • the channel encoder is configured to generate a Trellis representation of the parity former H p and to determine the parity bits p from the syndrome s by applying a Viterbi algorithm on the Trellis representation of the parity former H p .
  • the channel encoder is configured to use a cost function for the Viterbi algorithm, wherein the cost function is defined by, in particular identical to the first shaping constraint.
  • the parity former H p has a diagonal structure optimized for efficient parity forming, in particular a Trellis
  • an improved method is provided, allowing for encoding an information word into a shaped codeword in an efficient manner.
  • the invention relates to a computer program product with program code for performing the method according to the second aspect when executed on a computer.
  • the invention can be implemented in hardware and/or software.
  • FIG. 1 shows a schematic diagram illustrating a communication system comprising an encoder, a communication channel and a decoder
  • Fig. 2 shows a schematic diagram illustrating a communication system implementing a probabilistic amplitude shaping scheme
  • Fig. 3 shows a schematic diagram illustrating an encoder for probabilistic amplitude shaping
  • Fig. 4 shows a schematic diagram illustrating a channel encoder according to an embodiment
  • Fig. 5 shows a schematic diagram illustrating a method of encoding an information word according to an embodiment.
  • a disclosure in connection with a described method may also hold true for a corresponding device or system configured to perform the method and vice versa.
  • a corresponding device may include a unit to perform the described method step, even if such unit is not explicitly described or illustrated in the figures.
  • the features of the various exemplary aspects described herein may be combined with each other, unless specifically noted otherwise.
  • embodiments of the invention allow providing shaped parity bits, whereas the conventional probabilistic amplitude shaping (PAS) scheme has un-shaped parity bits.
  • Embodiments of the invention offer in particular the advantage of optimal shaping with integration of forward error correction (FEC) for any input distribution.
  • FEC forward error correction
  • Figure 4 shows a schematic diagram of a channel encoder 400 according to an embodiment.
  • the code word x contains the information word u and M + J parity bits p.
  • the first shaping constraint can be equal to the second shaping constraint.
  • the first shaping constraint requires that the number of 0 bits is substantially different from the number of 1 bits of the M + J parity bits p of the code word x.
  • the number of 0 bits can be substantially larger than the number of 1 bits of the M + J parity bits p of the code word x, wherein the channel encoder is further configured to map the M + J parity bits p to a plurality of signal points having at least one low energy level and one high energy level by mapping the 0 bits of the M + J parity bits p to the low energy level signal points.
  • the number of 1 bits can be substantially larger than the number of 0 bits of the M + J parity bits p of the code word x, wherein the channel encoder is further configured to map the M + J parity bits p to a plurality of signal points having at least one low energy level and one high energy level by mapping the 1 bits of the M + J parity bits p to the low energy level signal points.
  • the channel encoder 400 comprises a distribution matcher 401 that is configured to generate the information word u of length K - J bits on the basis of L data bits with K - J > L.
  • the channel encoder 400 is configured to encode the information word u of length K - J bits with K > J > 0 to a code word x of length N bits on the basis of a parity check matrix H, wherein the channel encoder 400 is configured to use the parity check matrix H in the following form:
  • H [H s , H p ] , wherein H s denotes a syndrome former 403 of size N - K) x ( K -/) and H p denotes a non-square full rank parity former 405 of size (N - K) x (N - K + /).
  • the parity check matrix H can define a linear forward error correction, FEC, code such that the FEC code has good error correcting capabilities. Also, the parity check matrix H can define a low-density parity check, LDPC, code.
  • the channel encoder 400 is configured to generate a Trellis representation of the parity former H p 405 and to determine the syndrome s by applying a Viterbi algorithm to the Trellis representation of the parity former H p 405.
  • the parity former H p 405 can have a diagonal structure optimized for efficient parity forming, in particular a Trellis representation of the parity former H p 405 with a reduced number of states.
  • the channel encoder 400 is configured to use a cost function for the Viterbi algorithm, wherein the cost function is defined by, in particular identical to the first shaping constraint.
  • the following shows in detail how the channel encoder 400 according to the embodiment enables efficient encoding of messages t into shaped code words x e S n C for linear codes C C F" and in general non-linear shaping sets S e F n by using the shaping FEC scheme.
  • the channel encoder 400 can divide the parity check matrix into the syndrome former H s 403 and the non-square M x (M + /) parity former H p 405 that has full row rank. As already mentioned above, for the parity bits p the encoder 400 can use the solution of the underdetermined linear equation:
  • p sH that fulfills the first shaping criteria, i.e., the resulting code word [ u, ] is in the shaping set and it is also a code word.
  • H p is non square.
  • the parity former 405 can then choose the solution that is optimal according to the first shaping criteria.
  • the parity former 405 can be implemented using existing algorithms, depending on the shaping criteria. For instance, when the shaping criteria require low weight, parity forming is equivalent to compressed sensing and appropriate algorithms can be used. When the shaping criteria require low weight, parity forming is equivalent to syndrome decoding and appropriate algorithms can be used.
  • a general parity forming matrix can be represented by a Trellis and syndrome decoding can be implemented by running the Viterbi algorithm on the trellis.
  • a general shaping criterion can be implemented by running the Viterbi algorithm on the Trellis.
  • the channel encoder 400 can generate a final output, i.e. the code word x by combining the output of the distribution matcher 401 and the output of the parity former 405 via a multiplexer 407.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Probability & Statistics with Applications (AREA)
  • Theoretical Computer Science (AREA)
  • Error Detection And Correction (AREA)

Abstract

L'invention concerne un codeur de canal (400) configuré pour coder un mot d'information u de longueur K -J bits avec K > J > 0 en un mot de code x de longueur N bits avec N - K = M > 0, le mot de code x contenant le mot d'information u etM + J bits de parité p, et le codeur de canal (400) est configuré pour mettre en œuvre un schéma de mise en forme probabiliste pour les M + J bits de parité p de telle sorte que le mot de code x = [u, p] est un mot de code d'un code linéaire C et les M + J bits de parité p satisfont une première contrainte de mise en forme.
PCT/EP2018/079286 2018-10-25 2018-10-25 Codeur de canal et procédé de codage d'un mot d'information WO2020083492A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201880098682.0A CN112840581B (zh) 2018-10-25 2018-10-25 信道编码器及用于编码信息字的方法
PCT/EP2018/079286 WO2020083492A1 (fr) 2018-10-25 2018-10-25 Codeur de canal et procédé de codage d'un mot d'information

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PCT/EP2018/079286 WO2020083492A1 (fr) 2018-10-25 2018-10-25 Codeur de canal et procédé de codage d'un mot d'information

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CN117014042A (zh) * 2022-04-28 2023-11-07 华为技术有限公司 一种通信方法、装置及系统

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EP3328012A1 (fr) * 2016-11-24 2018-05-30 Technische Universität München Procédé de conversion et de reconversion d'un signal de données et procédé et système de transmission de données et/ou de réception de données
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US20180083716A1 (en) * 2016-09-19 2018-03-22 Alcatel-Lucent Usa Inc. Probabilistic signal shaping and codes therefor
US10778366B2 (en) * 2017-03-31 2020-09-15 Qualcomm Incorporated Techniques for rate matching and interleaving in wireless communications
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EP3328012A1 (fr) * 2016-11-24 2018-05-30 Technische Universität München Procédé de conversion et de reconversion d'un signal de données et procédé et système de transmission de données et/ou de réception de données
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P. SCHULTE; G. BOCHERER: "Constant composition distribution matching", IEEE TRANS. INF. THEORY, vol. 62, 2016, pages 430, XP011594649, DOI: doi:10.1109/TIT.2015.2499181
RANA ALI AMJAD: "Information Rates and Error Exponents for Probabilistic Amplitude Shaping", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 16 February 2018 (2018-02-16), XP081235735 *
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